Pu Dandan, Xu Zikang, Sun Baoguo, Wang Yanbo, Xu Jialiang, Zhang Yuyu
Food Laboratory of Zhongyuan, Beijing Technology and Business University, Beijing 100048, China.
Key Laboratory of Geriatric Nutrition and Health Ministry of Education, Beijing Technology and Business University, Beijing 100048, China.
Foods. 2025 Apr 9;14(8):1302. doi: 10.3390/foods14081302.
Decoding the aroma composition plays a key role in designing and producing foods that consumers prefer. Due to the complex matrix and diverse aroma compounds of foods, isolation and quantitative analytical methods were systematically reviewed. Selecting suitable and complementary aroma extraction methods based on their characteristics can provide more complete aroma composition information. Multiple mass spectrometry detectors (MS, MS/MS, TOF-MS, IMS) and specialized detectors, including flame ionization detector (FID), electron capture detector (ECD), nitrogen-phosphorus detector (NPD), and flame photometric detector (FPD), are the most important qualitative technologies in aroma identification and quantification. Furthermore, the real-time monitoring of aroma release and perception is an important developing trend in the aroma perception of future food. A combination of artificial intelligence for chromatographic analysis and characteristic databases could significantly improve the qualitative analysis efficiency and accuracy of aroma analysis. External standard method and stable isotope dilution analysis were the most popular quantification methods among the four quantification methods. The combination with flavoromics enables the decoding of aroma profile contributions and the identification of characteristic marker aroma compounds. Aroma analysis has a wide range of applications in the fields of raw materials selection, food processing monitoring, and products quality control.
解析香气成分在设计和生产消费者喜爱的食品中起着关键作用。由于食品的基质复杂且香气化合物多样,对其分离和定量分析方法进行了系统综述。根据其特性选择合适且互补的香气提取方法可提供更完整的香气成分信息。多种质谱检测器(MS、MS/MS、TOF-MS、IMS)以及包括火焰离子化检测器(FID)、电子捕获检测器(ECD)、氮磷检测器(NPD)和火焰光度检测器(FPD)在内的专用检测器是香气鉴定和定量中最重要的定性技术。此外,对香气释放和感知的实时监测是未来食品香气感知的一个重要发展趋势。将人工智能用于色谱分析并结合特征数据库可显著提高香气分析的定性分析效率和准确性。外标法和稳定同位素稀释分析是四种定量方法中最常用的定量方法。与风味组学相结合能够解析香气特征贡献并鉴定特征性标记香气化合物。香气分析在原料选择、食品加工监测和产品质量控制等领域有着广泛应用。